Agricultural intensification reduces selection of putative plant growth-promoting rhizobacteria in wheat

Abstract The complex evolutionary history of wheat has shaped its associated root microbial community. However, consideration of impacts from agricultural intensification has been limited. This study investigated how endogenous (genome polyploidization) and exogenous (introduction of chemical fertilizers) factors have shaped beneficial rhizobacterial selection. We combined culture-independent and -dependent methods to analyze rhizobacterial community composition and its associated functions at the root–soil interface from a range of ancestral and modern wheat genotypes, grown with and without the addition of chemical fertilizer. In controlled pot experiments, fertilization and soil compartment (rhizosphere, rhizoplane) were the dominant factors shaping rhizobacterial community composition, whereas the expansion of the wheat genome from diploid to allopolyploid caused the next greatest variation. Rhizoplane-derived culturable bacterial collections tested for plant growth-promoting (PGP) traits revealed that fertilization reduced the abundance of putative plant growth-promoting rhizobacteria in allopolyploid wheats but not in wild wheat progenitors. Taxonomic classification of these isolates showed that these differences were largely driven by reduced selection of beneficial root bacteria representative of the Bacteroidota phylum in allopolyploid wheats. Furthermore, the complexity of supported beneficial bacterial populations in hexaploid wheats was greatly reduced in comparison to diploid wild wheats. We therefore propose that the selection of root-associated bacterial genera with PGP functions may be impaired by crop domestication in a fertilizer-dependent manner, a potentially crucial finding to direct future plant breeding programs to improve crop production systems in a changing environment.

Wheat species chosen for the current study.S3.Phyla from culture-independent amplicon sequence variant (ASV) datasets from non-fertilized rhizosphere, rhizoplane, and fertilized rhizosphere, rhizoplane wheat samples.

Data S1. Statistical analysis of alpha diversity metrics.
See the Supplementary Data file: Data S1 (XLSX).[6] contributing the A and B portions of the AABB genome.Wild relatives of wheat were cultivated over a thousand-year period resulting in domesticated diploid T. monococcum (Einkorn), and tetraploid T. turgidum ssp.dicoccom (Emmer), carthlicum, polonicum, and turanicum.The final hybridization event between tetraploid wheat (AABB) and Ae.tauschii (DD) is thought to have occurred only once or twice, ~8000-10,000 years ago, resulting in the hexaploid (AABBDD) wheat species, T. aestivum [5], most used in the production of bread including ssp.macha and spelta.Significant yield gains were achieved by wheat breeders via the exploitation of genetic variation that arose via gene mutation resulting in commercial cultivars T. aestivum cv.Chidham White Chaff (1790), Red Lammas (1850), and Victor (1908).During the Green revolution (1960s), mutant alleles of the Reduced height (Rht) dwarfing genes [7] were introduced into modern wheat cultivars resulting in plant height reduction which led to the commercial cultivars Avalon (1980), Hereward (1989), Cadenza (1992), Malacca (1997), Gallant (2009), and Crusoe (2012).Text highlighted in bold represent cultivars used in the study (adapted from Tkacz et al. [8]); numbers refer to Table S1.

Fig S2.
Functional bioassay analysis to identify bacterial isolates with plant growth-promoting (PGP) traits.Diagram depicts methodology for one soil sample.Colonies previously picked from diluted rhizoplane samples spread on agar were grown in 10% tryptone soya broth in 96well plates; 94 colonies were picked with one colony per well, wells H11 and H12 were left uninoculated as negative control wells.Isolates were then spot inoculated using a 96-prong inoculating manifold onto: 10% tryptone soya agar for confirmation of bacterial growth, casein agar [9], Pikovskaya agar [10], Aleksandrov agar with potash feldspar as the potassium source [11], chrome azurol S (CAS) agar [12,13], and zinc agar (HiMedia M2023) to test for casein, phosphate, potassium, iron, and zinc solubilization, respectively.Positive responses were recorded in the depicted table format and isolates testing positive for any two of the five traits tested was defined as a putative PGPR.The 96-well plate image is from biorender.com.Isolates previously identified to exhibit plant growth-promoting traits (PGPR; depicted in green) vs. isolates that displayed no functional traits (non-PGPR; depicted in yellow) were pipetted (100 l culture) from wells in a 96-well plate using custom scripts created on the Opentrons protocol designer (https://designer.opentrons.com) on the Opentrons OT-2 Lab Robot (Opentrons, Long Island City, NY, USA) and combined into single tubes, one for PGPR isolates and one for non-PGPR isolates.These were then subjected to genomic DNA extraction (for Gram-positive bacteria) and amplicon sequencing.S1).
Fig. S1.The evolution of plant breeding in wheat.

Fig. S5 .
Fig. S5.Photos of wheat species used in this study, taken at flowering stage.

Fig. S6 .
Fig. S6.Rarefaction curve analyses of bacterial species richness as a function of sequencingdepth for (A) all samples and (B) samples at a cut-off of 2,000 reads as used for downstream alpha diversity analysis for culture-independent samples.

Fig. S8 .
Fig. S8.Principal Coordinate Analysis (PCoA) plots of bacterial community based on Bray-Curtis distance in non-fertilized and fertilized rhizosphere (A) and rhizoplane (B) samples from diploid, tetraploid and hexaploid wheat varieties.

Fig. S9 .
Fig. S9.Canonical Analysis of Principal coordinates (CAP) plots of bacterial composition based on Bray-Curtis distance with ploidy level as the factor of constraint; p-values are from permutation tests (ANOVA; capscale under a reduced model).

Fig. S10 .
Fig. S10.PCoA plots of bacterial community based on Bray-Curtis distance in non-fertilized (A) and fertilized (B) rhizosphere and rhizoplane samples from diploid, tetraploid and hexaploid wheat varieties.
Figure was created in biorender.com.

Fig. S5 .
Fig. S5.Photos of wheat species used in this study, taken at flowering stage.

Fig. S6 .
Fig.S6.Rarefaction curve analyses of bacterial species richness as a function of sequencing depth for (A) all samples and (B) samples at a cut-off of 2,000 reads as used for downstream alpha diversity analysis for culture-independent samples.

Fig. S7 .
Fig. S7.Average dry plant biomass (A), ear length (B), and height (C) of wild wheat progenitors (AA, BB, DD) and allopolyploid (AABB, AABBDD) wheats grown in nutrientdepleted agricultural soil with and without fertilizer addition.Bars represent mean values for all 19 plant varieties (Triticum and Aegilops) from 4 biological replicates (left column) and for each wheat genome (right column) with individual samples shown as data points; error bars show the standard deviation.Statistical influences of genome level and fertilization were determined by Kruskal-Wallis tests.Plant height was measured from soil surface to head of longest stem, the longest ear of the plant was measured for ear length, and plant biomass was measured by dry foliar biomass.

Fig. S8 .Fig. S9 .Fig. S10 .
Fig. S8.Principal Coordinate Analysis (PCoA) plots of bacterial community based on Bray-Curtis distance in non-fertilized and fertilized rhizosphere (A) and rhizoplane (B) samples from diploid, tetraploid and hexaploid wheat varieties.The percentage shown in each axis corresponds to the proportion of variation explained.

Fig. S11 .
Fig. S11.CAP analysis of the bacterial rhizosphere (A, E, I) and rhizoplane (B, F, J) community from non-fertilized wheat (first two columns) and the bacterial rhizosphere (C, G, K) and rhizoplane (D, H, L) community for fertilized wheat (last two columns) using ancestral class (A-D), genome (E-H), and plant species (I-L) as the factors of constraint; P values are from permutation tests (ANOVA; capscale under a reduced model).The percentage shown in each axis corresponds to the proportion of variation explained.
Fig. S12.Analysis of culturable bacterial abundances isolated from soil (unplanted and rhizoplane) samples collected from diploid wheat progenitors (AA, BB, DD), tetraploid (AABB) and hexaploid (AABBDD) wheats, grown with and without the addition of NPK fertilizer granules, as well as unplanted control pots.Plots of (A) predicted means with average least significant difference bars at 5% and (B) back transformed means with 95% confidence intervals (CI), calculated from negative binomial generalized linear models (glms) with genotype and fertilization as factors from the proportion of bacteria with corresponding nutrient acquisition traits.

Fig. S13 .
Fig. S13.Classification of phyla abundances in culturable bacterial communities isolated from soil (unplanted and rhizoplane) from diploid wheat progenitors (AA, BB, DD), tetraploid (AABB) and hexaploid (AABBDD) wheats, grown with and without the addition of NPK fertilizer granules, as well as unplanted control pots.Phyla percentages were calculated from 16S rRNA gene ASV counts (PGPR and non-PGPR) which were used to determine the absolute abundance of each phylum based on total bacterial abundance.

Table S2 .
Soil properties from Woburn bare fallow soil sampled in April 2019.

Table S2 .
Soil properties from Woburn bare fallow soil sampled in April 2019.